Indel Detection
Indel Detection - Related Videos
04:34
Digital Droplet Polymerase Chain Reaction for Indel Mutation Detection in Target Genes
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2025
This video demonstrates the role of digital droplet polymerase chain reaction in identifying indel mutation in a DNA sample. The high precision and sensitivity of ddPCR enable accurate and consistent detection of rare mutations present in a sample, even at low levels. It can identify and quantify indel mutations in different regions of the genome, providing valuable insights into the mechanisms of mutation and the functional consequences of these mutations.
05:51
Digital-Droplet PCR to Detect Indels Mutations in Genetically Modified Anopheline Mosquito Populations
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Cited by 3 •
2021
This protocol provides the steps from DNA extraction to experimental set-up for digital droplet PCR (ddPCR), including analysis for the identification and quantification of non-homologous end-joining (NHEJ) events at target sites following gRNA-induced Cas9 cleavage and DNA repair. Other uses of this method include applications such as polymorphism detection and gene-editing variant verification.
05:30
Indel Detection following CRISPR/Cas9 Mutagenesis using High-resolution Melt Analysis in the Mosquito Aedes aegypti
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Cited by 4 •
2021
This article details a protocol for rapid identification of indels induced by CRISPR/Cas9 and selection of mutant lines in the mosquito Aedes aegypti using high-resolution melt analysis.
09:10
Combination of Adhesive-tape-based Sampling and Fluorescence in situ Hybridization for Rapid Detection of Salmonella on Fresh Produce
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Cited by 17 •
2010
This protocol describes a simple adhesive-tape-based approach for sampling of tomato and other fresh produce surfaces, followed by rapid whole cell detection of Salmonella using fluorescence in situ hybridization (FISH).
14:06
Detection of Rare Genomic Variants from Pooled Sequencing Using SPLINTER
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Cited by 10 •
2012
Pooled DNA sequencing is a fast and cost-effective strategy to detect rare variants associated with complex phenotypes in large cohorts. Here we describe the computational analysis of pooled, next-generation sequencing of 32 cancer-related genes using the SPLINTER software package. This method is scalable, and applicable to any phenotype of interest.
FAQs
The key signal is a mismatch between sequencing reads and the reference genome: reads may show a gap, a shifted placement, or a local change in read depth. These patterns indicate where an insertion or deletion may occur, but they require additional evaluation because alignment artifacts can create similar signals.
Quality scores estimate confidence in individual sequencing observations, while local sequence assembly reconstructs the region around a suspected variant. Combining these sources helps distinguish a consistent indel signal from errors introduced during sequencing or read alignment. This evaluation is important before a finding is interpreted as a genuine genetic variant.
The biological consequence depends strongly on genomic context. An indel in a coding region can alter the reading frame, whereas a change in a regulatory region may affect gene control. The resulting sequence change can also modify the protein product, so interpretation must consider location rather than simply recording the variant’s presence.
A basic workflow starts with sequencing data, aligns reads to a reference genome, and examines local gaps, placement shifts, or read-depth changes. Candidate sites are then assessed using read quality and local sequence assembly. This staged evaluation helps convert an initial computational signal into a more reliable indel call for downstream genetic analysis.
Indel detection can support investigations of gene function, inherited disease, cancer genomes, and genome-editing outcomes. The relevant question differs by setting: studies may ask whether a variant disrupts a coding frame, marks disease-associated variation, occurs in a tumor genome, or reflects an intended editing event. Reliable characterization strengthens these interpretations.
A candidate call provides evidence that the observed sequencing pattern is compatible with an insertion or deletion at a genomic location. It does not, by itself, establish functional impact. Researchers must relate the location to coding or regulatory sequence and consider whether the supporting evidence is strong enough to exclude sequencing or alignment error.